Customize Consent Preferences

We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.

The cookies that are categorized as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... 

Always Active

Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.

No cookies to display.

Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.

No cookies to display.

Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.

No cookies to display.

Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.

No cookies to display.

Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.

No cookies to display.

Skip to content

A blog on experiences with Machine Learning experiments

This blog covers some basics, experiments and related math in the field of Machine Learning [ML]. It is a personal blog and not an ordered book. Contents comes with numerical experiments I had some fun with.

I write in general about experiments which one can perform on a medium equipped Linux PC. Meaning: This blog will mainly cover conventional experiments which can e.g. be done with Scikit-Learn and Neural Networks with a rather limited number of layers. Still, I think that one can learn quite a lot of interesting things from such limited experiments.

Besides the fun factor: One can prepare oneself via studying some basics for bigger and more professional tasks.

For the time being this post is not yet about GPT and other advanced transformer based neural networks. The reason is simply that I need a new graphics card to perform related experiments. I will order one soon.

Who is this blog for?

I expect this blog to be interesting for people who have already started with private ML projects – but are no experts, yet. There is a variety of standard experiments one typically starts with. You will sooner or later find such experiments with variations here in this blog. But I also intend to cover some experiments which you may not find in introductory text books. So, the posts will cover topics both for beginners and advanced users of Python, Numpy, Scikit-Learn Keras and Tensorflow. I will try to point out what level of knowledge may be required to understand a post or a post series.

You are invited to ask questions, write comment and exchange experiences. However, I expect that you open an account on this blog and let me check your comments before publishing them.

Equipment to do your own experiments

If you want to do similar projects as discussed here you should be prepared to have some 32 GB RAM and a Nvidia card with at least 4 to 8 GB of VRAM. My personal programming environment are Jupyter Lab (for Python) and Eclipse with PyDev. I strongly advice you not to work with Jupyter, only. Instead you should systematically gather and reorder your work with neural networks systematically within classes and reusable methods. And you should collect your classes in suitable Python modules. An Eclipse/PyDev environment in my opinion is much more suitable for such tasks than Juypter.

I do all my ML experiments on Linux systems. Please, do not expect me to answer questions regarding PyDev and Jupyter installations on Windows.

Some math

What may distinguish this post from others is that I sometimes will write about mathematical aspects I stumble across during my experiments and which I find interesting. I will try to confine posts within a separate main category.

Most of the mathematical subjects I have so far looked into deal with linear algebra (matrix operations), some features of statistical multivariate normal distributions, ellipsoids and ellipses.
Further topics will follow.

The role of my linux-blog

Some people may know me from my linux-blog hosted at anracom.com. In the linux-blog I wrote about Linux- and LAMP-related topics the first years (up to 2014). During the last 10 years, however, the linux-blog has become a container for all kind of IT-topics.

Among other things it got a growing section for Machine Learning. As some readers of the linux-blog have recently complained about an overload of only partially Linux-related topics I have opened this new blog. I intend to transfer selected ML-related posts from the linux-blog to this new blog.